To carry out their activities, Research Teams of the Frédéric Joliot Institute for Life Sciences have developed high-profile technological platforms in many areas : biomedical imaging, structural biology, metabolomics, High-Throughput screening, level 3 microbiological safety laboratory...
All the news of the Institute of life sciences Frédéric Joliot
Scientific result | Article | MRI | Physics
A NeuroSpin team (BAOBAB) has tested a signal denoising method dedicated to very high field (7T) functional MRI. It is based on the weighted combination of images from each reception channel of the radio frequency coil, a combination that optimizes the stability of the signal over time.
In functional MRI (fMRI), thermal noise, head movements, scanner instabilities and physiological phenomena such as respiration and heartbeat can make signal changes due to neuronal activations difficult to detect reliably. Thus, the BOLD signal (signal depending on the cerebral oxygenation level) increases with the magnetic field intensity, but is only a few % above the background noise. Moreover, since the increase in spatial resolution is at the expense of the signal-to-noise ratio (SNR), it is necessary to develop image acquisition, reconstruction and denoising methods to improve the quality of the BOLD signal and push back the resolution limits. In standard use, fMRI images are acquired using radio frequency (RF) coils with multi-receive channels, which implies reconstruction of images channel by channel and thus obtaining of multiple images per time frame. The final image is calculated by the sum of the squares of each single channel image. However, this reconstruction is not optimal if we consider the temporal SNR (tSNR). The latter reflects the stability of the signal over time and is a more relevant indicator of the quality of fMRI data, since these data are the result of a temporal analysis of each voxel to detect the BOLD signal. In this study, conducted in fMRI in four volunteers on the NeuroSpin 7T imager, the researchers applied a new mathematical formula for combining channels to optimize the tSNR of the image. The results show a strong improvement of the tSNR, but a reduced BOLD sensitivity, as the tSNR does not dissociate the BOLD signal from the noise. Despite the proven optimality of the channel combination tested in this work for quality measurements, the BOLD activation maps are not improved compared to the reference channel combination. This study thus highlights the potential limitations of tSNR when assessing the quality of fMRI data. Contacts : Nicolas Boulant (firstname.lastname@example.org); Redouane Jamil email@example.com Study conducted within the framework of the H2020 AROMA program. To learn more on AROMA - The BOLD (blood-oxygen-level dependent) signal is the signal that reflects local and transient variations in the amount of oxygen transported by hemoglobin in response to neuronal activity in the brain. - The radiofrequency transceiver or RF coil excites the tissues and measures the signal at the origin of the images. Composed of several reception channels, the coils allow a better coverage of the imaged object and a reduced acquisition time. - The tSNR consists in mathematically evaluating the stability of the signal over time for each voxel via the ratio between the mean and the standard deviation of the time series. - Voxel: to build an image we "pixelate" the volume by subdividing it into small cubes called voxels for "volumetric pixels". The smaller the voxels, the higher the resolution of the image but the weaker the signal.
Redouane Jamil, Franck Mauconduit, Caroline Le Ster, Philipp Ehses, Benedikt A. Poser, Alexandre Vignaud, Nicolas Boulant.Temporal SNR optimization through RF coil combination in fMRI: The more, the better? Plos One, November 8, 2021 https://doi.org/10.1371/journal.pone.0259592
CEA is a French government-funded technological research organisation in four main areas: low-carbon energies, defense and security, information technologies and health technologies. A prominent player in the European Research Area, it is involved in setting up collaborative projects with many partners around the world.